TBNAI
Open Challenges and Opportunities in Human-Agent Systems
Publication: cs.AI updates on arXiv.org
Author: Reuth Mirsky, Sarath Sreedharan, Nitay Alon, Stefan Sarkadi, Munindar P. Singh, Liz Sonenberg, Peter Stone, Silvia Tulli, Stylianos Loukas Vasileiou, Shlomo Zilberstein
Source published: 13/11/2026, 05:00:00 UTC
Briefing created: 13/11/2026, 08:09:00 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 13/11/2026, 07:48:25 UTC.
Briefings
A recent paper by the AAMAS community examines how agentic AI systems interact with humans, emphasizing the need for theories of mind and recursive reasoning to handle uncertainty and conflicting objectives. The study analyzes various interaction scales from individual partnerships to large teams, proposing computational frameworks that support cooperative inverse reinforcement learning and argumentation. This research provides foundational insights for designing systems that account for evolving human knowledge and intentions.
Key points
- The paper analyzes interactions ranging from individual human-agent partnerships to teams and larger groups, where participants differ in roles, decision authority, and capabilities.
- The authors propose that progress requires treating human interaction as an ongoing decision problem shaped by uncertainty, interdependence, and potentially conflicting objectives.
Context
Agentic AI systems increasingly undertake extended tasks and act on people's behalf, making human-agent interaction central to their effectiveness. This paper examines how foundations developed by the Autonomous Agents and Multi-Agent Systems (AAMAS) community inform these demands.
Limitations
The evidence is a preprint from arXiv:2611.14846v1, which may not yet be fully peer-reviewed. The study relies on theoretical frameworks and computational approaches rather than empirical data or field experiments. Specific quantitative results or long-term impact metrics are not provided in the available text.
Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 13/11/2026, 08:09:00 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.
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